Self-efficacy of Saudi English Majors after the Emergent Transition to Online Learning and Online Assessment during the COVID-19 Pandemic
Bibliographic record
Abstract
This research explores the sense of self-efficacy among Saudi English majors at Jeddah University during the COVID-19 pandemic, which forced all schools in Saudi Arabia to suspend face-to-face learning and, instead, use the online Blackboard platform. The study’s objectives are to determine Blackboard’s effect on Saudi learners’ self-efficacy beliefs, identify factors influencing these beliefs in the online context, and determine the relationship between self-efficacy beliefs and academic performance. Phone interviews, an online questionnaire, and online performance tests served as data collection instruments. The results indicate that urgent Blackboard use negatively affected the subjects’ self-efficacy beliefs, and there is a positive, significant relationship between academic performance and perceived self-efficacy. Among other factors, familiarity with Blackboard, technical competence, and a readiness to embrace technology strongly influenced the students’ self-efficacy beliefs. This paper also presents implications and pedagogical recommendations drawn from the results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".